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» Fast algorithms for time series mining
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ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
15 years 6 months ago
Clustering Distributed Time Series in Sensor Networks
Event detection is a critical task in sensor networks, especially for environmental monitoring applications. Traditional solutions to event detection are based on analyzing one-sh...
Jie Yin, Mohamed Medhat Gaber
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
15 years 5 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
SDM
2010
SIAM
202views Data Mining» more  SDM 2010»
14 years 10 months ago
Multiresolution Motif Discovery in Time Series
Time series motif discovery is an important problem with applications in a variety of areas that range from telecommunications to medicine. Several algorithms have been proposed t...
Nuno Castro, Paulo J. Azevedo
PKDD
2009
Springer
155views Data Mining» more  PKDD 2009»
15 years 6 months ago
Dynamic Factor Graphs for Time Series Modeling
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Piotr W. Mirowski, Yann LeCun
SDM
2009
SIAM
130views Data Mining» more  SDM 2009»
15 years 9 months ago
FuncICA for Time Series Pattern Discovery.
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...
Alexander Gray, Nishant Mehta